This will count as one of your downloads.
You will have access to both the presentation and article (if available).
Methods: A total of 60 cases were presented to the readers, of which 20 contained cancers and 40 showed no abnormality. Each case comprised of four images and 129 breast readers participated in the study. Each reader was asked to identify and locate any malignancies using a 1-5 confidence scale. All images were displayed using 5MP monitors, supported by radiology workstations with full image manipulation capabilities. A jack-knife free-response receiver operating characteristic, figure of merit (JAFROC, FOM) methodology was employed to assess reader performance. Details were obtained from each reader regarding their experience, qualifications and breast reading activities. Spearman and Mann Whitney U techniques were used for statistical analysis.
Results: Higher performance was positively related to numbers of years professionally qualified (r= 0.18; P<0.05), number of years reading breast images (r= 0.24; P<0.01), number of mammography images read per year (r= 0.28; P<0.001) and number of hours reading mammographic images per week (r= 0.19; P<0.04). Unexpectedly, higher performance was inversely linked to previous experience with digital images (r= - 0.17; p<0.05) and further analysis, demonstrated that this finding was due to changes in specificity.
Conclusion: This study suggests suggestion that readers with experience in digital images reporting may exhibit a reduced ability to correctly identify normal appearances requires further investigation. Higher performance is linked to number of cases read per year.
Sixty radiographs were obtained by adjusting mAs to compensate for varying combinations of source-to-image distance (SID), kVp and patient thicknesses. The 25% rule, the DuPont™ Bit System and the DigiBit system were compared to determine which of these three most accurately predicted the mAs required for an increase in patient thickness. Similarly, the 15% rule, the DuPont™ Bit System and the DigiBit system were compared for an increase in kVp. The exposure index (EI) was used as an indication of exposure to the DDR. For each exposure combination the mAs was adjusted until an EI of 1500+/-2% was achieved.
The 25% rule was the most accurate at predicting the mAs required for an increase in patient thickness, with 53% of the mAs predictions correct. The DigiBit system was the most accurate at predicting mAs needed for changes in kVp, with 33% of predictions correct.
This study demonstrated that the 25% rule and DigiBit system were the most accurate predictors of mAs required for an increase in patient thickness and kVp respectively. The DigiBit system worked well in both scenarios as it is a single exposure adjustment system that considers a variety of exposure factors.
Mammographic density measurement: a comparison of automated volumetric density measurement to BIRADS
Publisher’s Note: This paper, originally published on 3/11/14, was replaced with a corrected/revised version on 8/1/14. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Background: The performance of screen readers in detecting breast cancer is being assessed in some countries by using mammographic test sets. However, previous studies have provided little evidence that performance assessed by test sets strongly correlate to performance in clinical reading.
Methods: Five clinicians from BreastScreen New South Wales participated in this study. Each clinician was asked to read 200 de-identified mammographic examinations gathered from their own case history within the BreastScreen NSW Digital Imaging Library. All test sets were designed with specific proportions of true positive, true negative, false positive and false negative examinations from the previous actual clinical reads of each reader. A prior mammogram examination for comparison (when available) was also provided for each case.
Results: Preliminary analyses have shown that there is a moderate level of agreement (Kappa 0.42−0.56, p < 0.001) between laboratory test sets and actual clinical reading. In addition, a mean increase of 38% in sensitivity in the laboratory test sets as compared to their actual clinical readings was demonstrated. Specificity is similar between the laboratory test sets and actual clinical reading.
Conclusion: This study demonstrated a moderate level of agreement between actual clinical reading and test set reading, which suggests that test sets have a role in reflecting clinical performance.
The effect of image interpretation training on the fracture recognition performance of radiographers
View contact details
No SPIE Account? Create one
